Zobrazeno 1 - 10
of 336
pro vyhledávání: '"Narayanan, P. J."'
Autor:
Saini, Saurabh, Narayanan, P J
We present a new additive image factorization technique that treats images to be composed of multiple latent specular components which can be simply estimated recursively by modulating the sparsity during decomposition. Our model-driven {\em RSFNet}
Externí odkaz:
http://arxiv.org/abs/2404.01998
Autor:
Gupta, Avani, Narayanan, P J
The focus of recent research has shifted from merely improving the metrics based performance of Deep Neural Networks (DNNs) to DNNs which are more interpretable to humans. The field of eXplainable Artificial Intelligence (XAI) has observed various te
Externí odkaz:
http://arxiv.org/abs/2403.14566
Traditional Radiance Field (RF) representations capture details of a specific scene and must be trained afresh on each scene. Semantic feature fields have been added to RFs to facilitate several segmentation tasks. Generalised RF representations lear
Externí odkaz:
http://arxiv.org/abs/2402.04632
Stylized view generation of scenes captured casually using a camera has received much attention recently. The geometry and appearance of the scene are typically captured as neural point sets or neural radiance fields in the previous work. An image st
Externí odkaz:
http://arxiv.org/abs/2212.09330
Precomputed Radiance Transfer (PRT) is widely used for real-time photorealistic effects. PRT disentangles the rendering equation into transfer and lighting, enabling their precomputation. Transfer accounts for the cosine-weighted visibility of points
Externí odkaz:
http://arxiv.org/abs/2212.09315
Autor:
Gera, Pulkit, Dastjerdi, Mohammad Reza Karimi, Renaud, Charles, Narayanan, P. J., Lalonde, Jean-François
We present PanoHDR-NeRF, a neural representation of the full HDR radiance field of an indoor scene, and a pipeline to capture it casually, without elaborate setups or complex capture protocols. First, a user captures a low dynamic range (LDR) omnidir
Externí odkaz:
http://arxiv.org/abs/2208.07903
Autor:
Jinka, Sai Sagar, Srivastava, Astitva, Pokhariya, Chandradeep, Sharma, Avinash, Narayanan, P. J.
Recent advancements in deep learning have enabled 3D human body reconstruction from a monocular image, which has broad applications in multiple domains. In this paper, we propose SHARP (SHape Aware Reconstruction of People in loose clothing), a novel
Externí odkaz:
http://arxiv.org/abs/2205.11948
Precomputed Radiance Transfer (PRT) can achieve high quality renders of glossy materials at real-time framerates. PRT involves precomputing a k-dimensional transfer vector of Spherical Harmonic (SH) coefficients at specific points for a scene. Most p
Externí odkaz:
http://arxiv.org/abs/2203.12399
Linearly Transformed Cosines (LTCs) are a family of distributions that are used for real-time area-light shading thanks to their analytic integration properties. Modern game engines use an LTC approximation of the ubiquitous GGX model, but currently
Externí odkaz:
http://arxiv.org/abs/2203.11904
We present a neural rendering framework for simultaneous view synthesis and appearance editing of a scene from multi-view images captured under known environment illumination. Existing approaches either achieve view synthesis alone or view synthesis
Externí odkaz:
http://arxiv.org/abs/2110.07674